Unlocking Geothermal Potential: Advancing Exploration with Artificial Intelligence for Sustainable Energy Solutions

Abstract The objective of this study is to investigate the potential benefits and challenges of integrating Artificial Intelligence (AI) into geothermal exploration for resource identification and drilling location optimization. The scope includes investigating the application of AI algorithms in the analysis of subsurface datasets to improve prediction accuracy and reduce uncertainty in geothermal resource evaluation. A critical review of published articles on AI applications in the geothermal industry was conducted to gain insight into the effectiveness of AI models in resource exploration. Various AI algorithms such as Logistic Regression, Artificial Neural Networks and Decision Tree were analyzed for their contributions to geophysical and geochemical data analysis in geothermal exploration. The review focused on the identification of hidden patterns in large datasets using AI algorithms to improve the understanding of subsurface properties and to locate hidden/blind geothermal systems. The analysis involved evaluating the performance of different AI techniques in predicting reservoir properties, lithology and fluid content based on geochemical and geophysical data. The results of the study demonstrate the significant potential of AI in improving the accuracy of predicting geothermal reservoir properties and optimizing drilling locations. AI models outperformed traditional expert-based and statistical methods, demonstrating their effectiveness in uncovering hidden geothermal resources and reducing exploration risks. Observations from the review highlight the importance of collaboration and partnerships within the geothermal industry to leverage multiple datasets and insights for improved efficiency and productivity in energy development. While there are challenges such as model transferability between locations, the continued growth of AI in geothermal exploration provides opportunities for further research and development of deep learning techniques. The increasing use of AI in geothermal exploration indicates a shift towards data-driven decision making and advanced predictive modelling techniques.